U.S. patent number 6,504,506 [Application Number 09/607,733] was granted by the patent office on 2003-01-07 for method and device for fixed in time adaptive antenna combining weights.
This patent grant is currently assigned to Motorola, Inc.. Invention is credited to Timothy A. Thomas, Frederick W. Vook.
United States Patent |
6,504,506 |
Thomas , et al. |
January 7, 2003 |
Method and device for fixed in time adaptive antenna combining
weights
Abstract
A receiving device and method for operating a communication
system are provided. The receiving device receives at least one
Doppler channel estimate for at least one transmitter and a spatial
covariance matrix of a corrupting environment. The Doppler channel
estimates are used to create a Null Doppler spatial covariance
matrix. A total Doppler spatial covariance matrix is created as a
sum of the spatial covariance matrix of the corrupting environment,
plus the Doppler spatial covariance matrix. A combining weight for
at least one transmitter and at least one Doppler channel is
created from the total Doppler spatial covariance and the at least
one Doppler channel for the at least one transmitter.
Inventors: |
Thomas; Timothy A. (Palatine,
IL), Vook; Frederick W. (Schaumburg, IL) |
Assignee: |
Motorola, Inc. (Schaumburg,
IL)
|
Family
ID: |
24433497 |
Appl.
No.: |
09/607,733 |
Filed: |
June 30, 2000 |
Current U.S.
Class: |
342/383;
342/367 |
Current CPC
Class: |
H04B
7/01 (20130101); H04B 7/0848 (20130101) |
Current International
Class: |
H04B
7/01 (20060101); H04B 7/08 (20060101); G01S
003/28 () |
Field of
Search: |
;342/361,367,378,383
;455/67.6,205 |
References Cited
[Referenced By]
U.S. Patent Documents
Other References
Article entitled "Adaptive Frequency-Domain Equalization and
Diversity Combining For Broadband Wireless Communications,"
(Author, Martin V. Clark, IEEE JSAC, vol. 16, pp. 1385-1395, Oct.
1998). .
Article entitled "Basis Expansions Models and Diversity Techniques
for Blind Identification and Equalization of Time-Varying
Channels," (Author Georgios B. Giannakis, Proc. IEEE, vol. 86, No.
10, pp. 1969-1986, Oct. 1998). .
Article entitled "Characterization of Fast Fading Vector Channels
for Multi-Antenna Communication Systems," (Authors Gregory Raleigh,
Suhas N. Diggavi, Ayman F. Naguib, Arogyaswami Paulraj, Proc. 28th,
Asilomar Conf., Pacific Grove Ca, 5 pp., Nov. 1994). .
Article entitled "Deterministic Approaches for Blind Equalization
of Time-Varying Channels with Antenna Arrays," (Authors Hui Liu,
Georgios B. Giannakis, IEEE Trans on Sig. Proc., vol. 46, No. 11,
pp. 3003-3013, Nov. 1998). .
Article entitled "Least-Squares Multi-User Frequency-Domain Channel
Estimation for Broadband Wireless Communication Systems," (Authors
Timothy A. Thomas, Fred W. Vook and Kevin L. Baum, 37th Allerton
Conference, Monticello, IL, 10 pp., Sep. 1999). .
Article entitled "Linear and Nonlinear Programming," (Author David
G. Luenberger, Addison-Wesley Publishing Company, Monlo Park, CA,
pp. 215-216, 1989). .
Article entitled "Multicarrier Modulation for Data Transmission: An
Idea Whose Time Has Come," (Author John A. C. Bingham, IEEE Comm.
Mag., vol. 28, pp. 5-14, May 1990). .
Article entitled "Robust Channel Estimation for OFDM Systems with
Rapid Dispersive Fading Channels," (Authors Ye G. Li, Leonard J.
Cimini, Jr., Nelson R. Sollenberger, IEEE Trans. On Comm., vol. 46,
pp. 902-915, Jul. 1998). .
Article entitled "Sinusoidal Model and Prediction of Fast Fading
Processes," (Authors Jeng-Kuang Hwang, Jack H. Winters, Globecom,
pp. 892-897, 1998). .
Article entitled "Space-Time Modems for Wireless Personal
Communications," (Author A. J. Paulraj, Boon C. Ng, IEEE Personal
Communications Magazine, pp. 36-48, Feb. 1998). .
Article entitled "Analysis of DFT-Based Channel Estimators for
OFDM*" (Authors Ove Edfors, Magnus Sandell, Jan-Jaap van de Beek,
Sara Kate Wilson, Per Ola Borjesson, This work has been presented
in part at the 1995 Vehicular Technology Conference (VTC '96) in
Chicago, Illinois, Jul. 25-28, 1995, pp. 815-819). .
Article entitled "Channel Estimation for OFDM Systems with
Transmitter Diversity in Mobile Wireless Channels" (Authors
Ye(Geoffrey) Li, Senior Member, IEEE, Nambirajan Seshadri, Senior
Member, IEEE, and Sirikiat Ariyavisitakul, Senior Member, IEEE, pp.
461-471, IEEE Journal on Selected Areas in Communications, vol. 17,
No. 3, Mar. 1999)..
|
Primary Examiner: Phan; Dao
Attorney, Agent or Firm: Fekete; Douglas D. Juffernbruch;
Daniel W.
Parent Case Text
This application is related to Ser. No.: 09/607,736 and 09/608,760,
both filed on Jun. 30, 2000.
Claims
We claim:
1. A method of operating a communication system comprising:
providing at least one Doppler channel estimate for at least one
transmitter and a spatial covariance matrix of a corrupting
environment; computing a Null Doppler spatial covariance matrix, as
a function of the Doppler channel estimates; computing a total
Doppler spatial covariance matrix as a sum of the spatial
covariance matrix of the corrupting environment plus the Doppler
spatial covariance matrix; and computing a combining weight at
subcarrier k for at least one transmitter and at least one Doppler
channel as a function of the total Doppler spatial covariance and
the at least one Doppler channel for the at least one
transmitter.
2. The method of claim 1 wherein the Null Doppler spatial
covariance matrix R(k) for at least one receiver is computed
according to ##EQU17##
3. The method of claim 1 wherein the total Doppler spatial
covariance matrix for at least one receiver is computed according
to R.sub.T (k)=R(k)+R.sub.c (k).
4. The method of claim 1 wherein the combining weight for at least
one Doppler channel is computed according to w.sub.u,v (k)=(R.sub.T
(k)).sup.-1 H.sub.u,v (k).
5. A method of operating a communication system including at least
one receiver comprising: providing the Doppler channel estimates
for at least one transmitter; determining a Doppler channel matrix
for the at least one transmitter G(k), using the Doppler channel
estimates; and computing a combining weight at subcarrier k for at
least one transmitter and at least one Doppler channel as a
function of the Doppler channel matrix for all desired
transmitters.
6. The method of claim 5 wherein a Doppler channel matrix for at
least one transmitter is determined according to (M.times.UV.sub.T)
G(k)=[H.sub.1,-V (k), . . . , H.sub.1,V (k), H.sub.2,-V (k), . . .
, H.sub.U,V (k)] wherein H.sub.U,V (k) is transmitter u's v.sup.th
frequency-domain Doppler channel.
7. The method of claim 5 wherein the weight for at least on
transmitter and at least one Doppler channel are computed according
to W(k)=G(k)(G.sup.H (k)G(k)).sup.-1.
8. A method of operating a communication system including at least
one receiver comprising: providing at least one Doppler channel
estimate for at least one transmitter, and a spatial covariance
matrix of a computing environment; providing a frequency
correlation function; computing a Doppler spatial covariance matrix
as a function of the Doppler channel estimate and the frequency
correlation function; computing a total Doppler spatial covariance
matrix as a sum of the spatial covariance matrix of the corrupting
environment plus the Doppler spatial covariance matrix; computing a
Doppler steering vector for the at least one transmitter and at
least one Doppler channel as a function of the Doppler channel
estimates and the frequency correlation function; and computing a
combining weight at subcarrier k for at least one transmitter and
at least one Doppler channel as a function of the total Doppler
spatial covariance and the Doppler steering vector for the at least
one transmitter and at least one Doppler channel.
9. The method of claim 8 wherein a Doppler spatial covariance
matrix for at least one receiver is computed according to
##EQU18##
wherein the frequency correlation function, .alpha..sub.b (v) is
##EQU19##
10. The method of claim 8 wherein a total Doppler spatial
covariance matrix for at least one receiver is computed according
to R.sub.T (k)=R(k)+R.sub.c (k) wherein R.sub.c (k) is the spatial
correlation matrix of the corrupting environment.
11. The method of claim 8 wherein a Doppler steering vector for at
lest one transmitter and at least one Doppler channel is computed
according to ##EQU20##
12. The method of claim 8 wherein a combining weight at subcarrier
k for at least one transmitter and at least one Doppler channel is
computed according to w.sub.u,v (k)=(R.sub.T (k)).sup.-1 p.sub.u,v
(k).
13. A receiver for a wireless communication system comprising:
means for providing at least one Doppler channel estimate for at
least one transmitter and a spatial covariance matrix of a
corrupting environment; means for computing a Null Doppler spatial
covariance matrix, as a function of the Doppler channel estimates;
means for computing a total Doppler spatial covariance matrix as a
sum of the spatial covariance matrix of the corrupting environment
plus the Doppler spatial covariance matrix; and means for computing
a combining weight at subcarrier k for at least one transmitter and
at least one Doppler channel as a function of the total Doppler
spatial covariance and the at least one Doppler channel for the at
least one transmitter.
14. A receiver for a wireless communication system comprising:
means for providing the Doppler channel estimates for at least one
transmitter; means for determining a Doppler channel matrix for the
at least one transmitter G(k), using the Doppler channel estimates;
and means for computing a combining weight at subcarrier k for at
least one transmitter and at least one Doppler channel as a
function of the Doppler channel matrix for all desired
transmitters.
15. A receiver for a wireless communication system comprising:
means for providing at least one Doppler channel estimate for at
least one transmitter, and a spatial covariance matrix of a
computing environment; means for providing a frequency correlation
function; means for computing a Doppler spatial covariance matrix
as a function of the Doppler channel estimate and the frequency
correlation function; means for computing a total Doppler spatial
covariance matrix as a sum of the spatial covariance matrix of the
corrupting environment plus the Doppler spatial covariance matrix;
means for computing a Doppler steering vector for the at least one
transmitter and at least one Doppler channel as a function of the
Doppler channel estimates and the frequency correlation function;
and means for computing a combining weight at subcarrier k for at
least one transmitter and at least one Doppler channel as a
function of the total Doppler spatial covariance and the Doppler
steering vector for the at least one transmitter and at least one
Doppler channel.
16. A computer readable medium storing a computer program
comprising: computer readable program code for providing at least
one Doppler channel estimate for at least one transmitter and a
spatial covariance matrix of a corrupting environment; computer
readable program code for computing a Null Doppler spatial
covariance matrix, as a function of the Doppler channel estimates;
computer readable program code for computing a total Doppler
spatial covariance matrix as a sum of the spatial covariance matrix
of the computing environment plus the Doppler spatial covariance
matrix; and computer readable program code for computing a
combining weight at subcarrier k for at least one transmitter and
at least one Doppler channel as a function of the total Doppler
spatial covariance and the at least one Doppler channel for the at
least one transmitter.
17. A computer readable medium storing a computer program
comprising: computer readable program code for providing the
Doppler channel estimates for at least one transmitter; computer
readable program code for determining a Doppler channel matrix for
the at least one transmitter G(k), using the Doppler channel
estimates; and computer readable program code for computing a
combining weight at subcarrier k for at least one transmitter and
at least one Doppler channel as a function of the Doppler channel
matrix for all desired transmitters.
18. A computer readable medium storing a computer program
comprising: computer readable program code for providing at least
one Doppler channel estimate for at least one transmitter, and a
spatial covariance matrix of a computing environment; computer
readable program code for providing a frequency correlation
function; computer readable program code for computing a Doppler
spatial covariance matrix as a function of the Doppler channel
estimate and the frequency correlation function; computer readable
program code for computing a total Doppler spatial covariance
matrix as a sum of the spatial covariance matrix of the corrupting
environment plus the Doppler spatial covariance matrix; computer
readable program code for computing a Doppler steering vector for
the at least one transmitter and at least one Doppler channel as a
function of the Doppler channel estimates and the frequency
correlation function; and computer readable program code for
computing a combining weight at subcarrier k for at least one
transmitter and at least one Doppler channel as a function of the
total Doppler spatial covariance and the Doppler steering vector
for the at least one transmitter and at least one Doppler channel.
Description
FIELD OF THE INVENTION
The present invention generally relates to the field of
communication systems and more particularly, to establishing the
adaptive antenna combining weights for at least one desired signal
received by at least one antenna for the purposes of receiving
transmitted data.
BACKGROUND OF THE INVENTION
In a wireless communication system, a major design challenge is to
maximize system capacity and performance in the presence of
interference, and a time-varying multipath channel. Multipath
propagation is caused by the transmitted signal reflecting off
objects near the transmitter and receiver and arriving at the
receiver over multiple paths. Interference in a communication
system can come from a variety of sources depending on the
particular system deployment. If the system is in motion, then
Doppler induced channel variations become an issue. Furthermore,
rapid channel variations can cause Doppler-induced Inter-Carrier
Interference (ICI) in the frequency-domain. Interference and
multipath are major factors that limit the achievable performance
and capacity of a communication system because both effects
interfere with the ability of a communication receiver to properly
decode the transmitted data.
In a multipath propagation channel, the transmitted signal
propagates to the receiver over a finite number L.sub.p of
propagation paths, where each path has an associated time delay and
complex gain. In such a channel, the communication receiver
receives the superposition of L.sub.p delayed, attenuated, and
phase-shifted copies of the transmitted signal. The number of paths
L.sub.p and their time delays and phase shifts depends on the
physical location of the various scattering objects (such as
buildings, automobiles, and trees) in the immediate vicinity of the
transmitter and receiver. The complex attenuation (magnitude and
phase) of each path depends on the length of each path, as well as
the material composition of any scatterers or reflectors
encountered along the path.
The presence of multipath can severely distort the received signal.
In a multipath environment, the multiple copies of the transmitted
signal can interfere constructively in some portions of the
occupied bandwidth. In other portions of the occupied bandwidth,
the multiple copies can interfere destructively at the receiver.
The signal duplication causes unwanted variations in the received
signal strength over the bandwidth occupied by the signal.
Furthermore, if the difference in the path delays of the various
propagation paths is significantly greater than the duration of a
transmitted information symbol, then intersymbol interference is
present at the receiver. When intersymbol interference is present,
the received signal is corrupted by prior transmitted symbols
propagating over paths having delays relative to the shortest path
that are longer than the duration of an information symbol. The
demodulation process (the process of determining which information
symbol was transmitted) becomes difficult in the presence of
intersymbol interference.
In a mobile wireless communication system, the complex attenuation
of each of the multipath components of the received signal becomes
a time varying function of the transmitter's path and speed
throughout the scattering field local to the transmitter's
position. The transmitter's motion causes the received signal
strength at a particular portion of the occupied bandwidth to vary
as time progresses. In a mobile multipath channel, the overall
channel response not only varies across the occupied bandwidth of
the signal, but also across time as well.
In addition to multipath, interference is another system component
that limits the performance of a communication system. If the
system is deployed in an unlicensed band, then other users of the
band can generate interference. And in a cellular system employing
frequency reuse, transmitters in another cell that is allocated the
same set of frequency channels can generate co-channel
interference. Frequency reuse is the practice of assigning the same
frequency channels to multiple users of the allocated spectrum.
Many cellular communication systems employ the technique of
frequency reuse in order to maximize the utilization of the
frequency spectrum allocated to a wide-area system deployment. In a
cellular system, a large geographical area is divided into smaller
regions called cells, where each cell is served by a single base
station operating on an assigned set of frequency channels. Within
each cell, multiple subscriber devices are allowed to communicate
with the base station on the frequency channels assigned to that
cell. The concept of frequency reuse involves allocating different
sets of frequency channels to the cells belonging to a particular
group and then reusing the same sets of frequencies to the cells
belonging to another group of cells.
The reuse factor of a cellular system is defined to be the minimum
distance between two cells that are allocated the same set of
frequency channels divided by the radius of a cell. A cellular
system employing a large reuse factor does not utilize the
allocated spectrum as efficiently as a cellular system employing a
smaller reuse factor. However, the level of co-channel interference
received by a receiver in the cellular system is directly dependent
on the reuse factor. Reducing the reuse factor tends to increase
the level of co-channel interference experienced by a receiver. To
better utilize the available spectrum, it would be advantageous to
be able to suppress the effects of co-channel interference.
To suppress co-channel interference, adaptive antenna signal
processing can be used. In a broadband wireless communication
system, adaptive antennas promise to increase system performance
and capacity by suppressing interference and providing a diversity
gain for equalization. Furthermore, adaptive antennas can increase
capacity through Spatial Division Multiple Access (SDMA), where
multiple subscriber devices share the same time-frequency channel
and are separated on the basis of their spatial channel responses.
However, for best performance, the adaptive antenna combining
algorithm must be able to compensate for time and frequency
variations in the channel responses of both the desired and
interference signals. Failure to correct for the channel variations
in either time or frequency will result in poor performance.
Thus, there is a need for a method and device for combining the
outputs of at least one receive antenna in the presence of severe
time variations in the channel response for the purposes of
equalization and interference suppression.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 is an overview diagram of a preferred embodiment of a
cellular communication system in accordance with the present
invention;
FIG. 2 is a block diagram illustrating a preferred embodiment of a
device in accordance with the present invention;
FIG. 3 is a block diagram illustrating details of the Antenna
Combiner of the device of FIG. 2;
FIG. 4 is a representation of an information burst for a
communication system with regular cyclic prefixes;
FIG. 5 is a flow chart representation of a preferred embodiment of
the method performed by the device of FIG. 2 for computing fixed in
time combining weights for any communication system, in accordance
with the present invention;
FIG. 6 is a flow chart representation of a preferred embodiment of
an alternative method performed by the device of FIG. 2 for
computing fixed in time combining weights for any communication
system, in accordance with the present invention; and
FIG. 7 is a flow chart representation of a preferred embodiment of
the method performed by the device of FIG. 2 for computing fixed in
time combining weights for communication systems with null cyclic
prefixes, in accordance with the present invention.
DETAILED DESCRIPTION OF THE PRESENTLY PREFERRED EMBODIMENTS
An adaptive antenna array is an array of antennas connected to a
communications receiver and operates by combining the signals
received by the antennas so as to optimize in an adaptive fashion
the receive characteristics of the array. By weighting and then
summing the multiple antenna signals, the adaptive antenna array
can adapt its angular response, sometimes called the array pattern,
while it operates in response to changes in the propagation
environment. While operating, the adaptive antenna attempts to
maximize the reception of the signal received from a desired
transmitting device, as it simultaneously minimizes the effects of
all other interfering signals and noise. In a communication system,
the interference suppression capability of an adaptive antenna
array offers the potential to reduce co-channel interference,
compensate for Inter-Carrier Interference (ICI), improve coverage
quality, and increase overall system capacity.
Adaptive antenna arrays also offer the possibility of providing a
new way of multiplexing multiple devices: Spatial Division Multiple
Access (SDMA). With SDMA, multiple devices can simultaneously share
the same channel (i.e., time, frequency, or code channel) and are
separated and simultaneously decoded by the receiver array on the
basis of their spatial position relative to the antenna array. When
successfully deployed, SDMA promises to provide enormous increases
in system capacity.
In addition, adaptive antenna arrays provide the ability to
increase system capacity through Multiple Input/Multiple Output
(MIMO) array processing techniques. The MIMO strategy involves
deploying multiple antennas on both the transmitter and the
receiver. In environments having rich multipath scattering, large
increases in capacity can be achieved through appropriate transmit
and receive signal processing techniques. An example MIMO strategy
calls for each antenna on the transmitter to transmit an
independent data stream, and the receive array must deploy SDMA
techniques to separate and decode the multiple transmitted
streams.
Spatial Division Multiple Access and Multiple Input/Multiple Output
are difficult technologies to implement because of the rapidly
varying multipath fading channel. In an SDMA system, the devices
that are sharing a channel provide interference to the receiver
processing algorithms that must decode the signals transmitted by
the devices. When a receiver-processing algorithm attempts to
decode one SDMA device, the other SDMA devices provide strong
interference to the decoding algorithm. The adaptive antenna
implementing SDMA suppresses the effects of the other devices when
attempting to decode one of the transmitting devices. In a MIMO
system, the multiple antennas of the transmitter interfere with
each other at the receive array, and the receiver has similar
difficulties as with an SDMA system.
A problem associated with employing both an equalizer and an
adaptive antenna in a wireless communication system lies in the
design of an algorithm and device having adequate ability to adapt
to changes in the signal environment. For best performance,
adaptive antennas that operate in a fast-fading multipath
environment must adapt to the rapidly varying channel as well as to
any changes in the nature of the desired and interfering signals.
In a broadband system, a frequency-selective multipath channel will
cause significant variations in the channel across the occupied
bandwidth of the received signal. Equalization and
interference-suppression algorithms, which cannot track these
channel variations both in time and frequency, will suffer
significant degradation in performance as measured by the Bit-Error
Rate (BER) or Signal-to-Interference-plus-Noise Ratio (SINR).
A common ingredient in many equalizers and adaptive antenna arrays
is an algorithm and device that estimates the characteristics of
the multipath propagation environment, channel transfer function,
or channel frequency response, between the desired transmitting
device and each of the at least one receiving antenna at the
communication receiver. When SDMA or MIMO is being employed in a
broadband system operating in a frequency-selective environment,
then an adaptive antenna array generally requires an estimate of
the channel frequency response between each receiving antenna and
each of the transmitting devices or antennas that are
simultaneously sending information to the array. The channel
estimation algorithm in this case should operate to simultaneously
solve for the channel responses of the multiple transmitting
devices or antennas. Performing a simultaneous estimate of the
channel responses of multiple transmitting devices is a difficult
operation in a mobile broadband communication system operating in a
multipath-rich environment with high frequency selectivity. Strong
interference caused by an SDMA or MIMO deployment, Doppler induced
ICI, or a low reuse factor causes even more difficulty to the
channel estimation algorithms. It would therefore be advantageous
for a device to be able to compute an accurate channel frequency
response estimate in the presence of SDMA interference, MIMO
interference, Inter-Symbol Interference (ISI), ICI, and co-channel
interference. It would also be advantageous for a device to be able
to track any variations in the channel frequency response of
multiple mobile users whose channel responses will vary as the
users move.
Given the need for higher system capacities in wireless
communication systems, adaptive antennas and advanced equalization
techniques are important for satisfying the ever-increasing need
for high data rate communications. To support the operation of
adaptive antennas and equalizers, it is advantageous to have a
method and device that tracks the time-varying frequency response
of a broadband system accurately enough to permit effective
equalization and interference suppression. Given the difficulties
associated with implementing SDMA and the deleterious nature of the
multipath-fading environment, such a device would enable improved
equalization and interference suppression performance in a mobile
broadband communication system.
Briefly described, the present invention is a method and device for
calculating the adaptive antenna combining weights for the at least
one transmitting device for the purposes of jointly equalizing the
at least one received signal, while simultaneously suppressing
interference in a communication receiver, in order to recover the
information transmitted by the at least one transmitting device. In
a highly frequency-selective mobile propagation channel, the
ability to accurately track the variations in the channel response
over both the time and frequency dimensions is critical to the
proper operation of any equalization or interference suppression
algorithm.
This invention utilizes channel estimates from an existing
estimation technique to compute the fixed in time adaptive antenna
combining weights that provide interference suppression and
compensate for Doppler induced variations (i.e., ICI). A novel
feature of the present invention is that a fixed (constant in time)
set of adaptive array combining weights are computed that are
highly effective at equalizing and suppressing interference in a
rapidly varying environment.
In order for adaptive antenna combining algorithms to be able to
equalize a desired user's signal and/or suppress interference in a
mobile wideband digital communication system, the channels of all
signals must be accurately tracked across frequency and in time.
The present invention's combining algorithms compensate for rapid
variations in the channel response and can even compensate for
severe channel variations within a data block, where a data block
is a group of received time-domain symbols that are transformed
into the frequency domain (e.g., with a Discrete Fourier Transform
(DFT)).
The method and device of the present invention can be incorporated
into a communications receiving device, base station, or subscriber
unit. In the present invention, the term "device " can refer to any
type of communications device such as a base station, subscriber
unit, or other communications receiver or transmitter.
The present invention is implemented in a communication system
where at least one desired transmitting device transmits
information to a communication receiver having at least one
antenna. In a preferred embodiment, pluralities of transmitting
devices simultaneously transmit information to a communication
receiver having a plurality of antennas. A transmitting device
transmits its information in bursts that contain two components: a
training interval and a data interval. The information transmitted
in a training interval contains pilot symbol sequences of content
and duration known by both the transmitting device and the
communication receiver. The data interval contains data symbols
also called blocks that must be recovered at the receiving device.
In the present invention, the term "burst " refers to any one of
the following: a short or isolated transmission, a portion of a
longer transmission, a portion of a continuous transmission, a
portion of a semi-continuous transmission, a time-limited
transmission, a bandwidth-limited transmission, or any combination
thereof.
The method and device of the present invention provides for a means
of weighting and summing the outputs of at least one receive
antenna to simultaneously receive and recover the information
transmitted simultaneously by at least one transmitting device.
Also if more than one antenna is present at the communication
receiver, then the method and device of the present invention can
be used to enable an adaptive antenna to mitigating the effects of
unwanted interference transmitted by other users of the occupied
bandwidth, as well as motion induced ICI, and ISI.
The ability to receive and recover the information transmitted
simultaneously by more than one device significantly increases the
capacity of the communication system. Conventional cellular systems
permit only one device to transmit on a particular frequency
channel within a cell for any predetermined time interval.
Providing for more than one device to transmit to a base station on
the same frequency channel at the same time will multiply the
capacity of the system by a factor equal to the number of devices
that are allowed to simultaneously transmit. Devices incorporating
algorithms for providing this capability must have the ability to
compensate for time and frequency variations in each desired
transmitter's and each interferer's channel. The method and device
of the present invention provide fixed in time adaptive antenna
interference suppression and equalization, utilizing new combining
weight techniques, making communication systems more efficient.
A preferred embodiment of the present invention described below
typically operates in a time-varying delay-spread channel and
operates under the assumption that the channel can change
significantly over the occupied bandwidth and significantly in
time. This invention requires channel estimates from a multi-user
channel estimation technique that tracks the time and frequency
variations of multiple transmitting devices (or antennas) sharing
the same time frequency channel.
One limiting factor to the implementation of adaptive antenna
combining weights in broadband communications is ISI, which can
cause severe frequency selectivity. Equalizing or suppressing
interference in a broadband channel with traditional time-domain
techniques becomes a complex problem when the channel length
becomes much larger than the symbol time. As a result, Orthogonal
Frequency Division Multiplexing (OFDM) and frequency-domain
equalization techniques have been proposed to combat the high level
of ISI that is typical in broadband channels.
An additional problem occurs when the end-users are mobile. The
speed of the mobiles causes significant time variations
necessitating combining weights that compensate for the variations
in the desired transmitter's and unknown interferer's channels. The
present invention uses a conceptual model that characterizes the
time-varying channel between a single transmit and single receive
antenna as the sum of multiple time-invariant channels called
"Doppler " channels. This is done through the following equation:
##EQU1##
time n for desired transmitting device u for l=0. . . L-1, N.sub.k
is the Doppler DFT size (typically N.sub.k is chosen to be twice
the length of the number of time-domain samples in an information
burst), and h.sub.u,v (n) is the v.sup.th time-domain Doppler
channel for user u.
The method and device of the present invention uses the
time-invariant Doppler channel estimates for each user to get
Minimum Mean Squared Error (MMSE) fixed in time adaptive antenna
combining weights. The first set of fixed in time weights, called
the Null Doppler weights, null out all Doppler channels except the
v.sup.th Doppler channel for user u. The second set of fixed in
time weights, called the Zero-Forcing Doppler weights, again null
out all Doppler channels except the v.sup.th Doppler channel for
user u. However, in many cases, the Zero-Forcing Doppler weights
are less computationally complex with similar BER performance as
the Null Doppler weights. The third set of weights are fixed in
time weights that are the solution to a Minimum Mean Squared Error
(MMSE) criteria and thus have better performance than the
Zero-Forcing Doppler or Null Doppler weights. An important
advantage of all of the fixed in time combining weights is that
they greatly reduce the computational complexity over combining
weights that are computed at each data block.
FIG. 1, numeral 100, illustrates a wireless communication system in
accordance with the preferred embodiment of the present invention.
As shown in FIG. 1, a Base Station 110 provides communication
service to a geographic region known as a cell 103. At least one
User Devices 120 and 130 communicate with the Base Station 110. In
some embodiments of the communication system of FIG. 1, at least
zero External Interference Sources 140 share the same spectrum
allocated to the base station 110 and subscriber devices 120 and
130. The External Interference Sources 140 represent an unwanted
source of emissions that interferes with the communication process
between the Base Station 110 and the User Devices 120 and 130. The
exact nature and number of the External Interference Sources 140
will depend on the specific embodiment of the communication system
of FIG. 1. In some cases, as is shown in FIG. 1, an External
Interference Source will be another User Device 140 (similar in
construction and purpose to User Device 120) that is communicating
with another Base Station 112 in the same frequency spectrum
allocated to Base Station 110 and User Devices 120 and 130. As
shown in FIG. 1, User Devices 120 has a single antenna, while User
Devices 130 have at least one antenna. The method and device of the
present invention can be implemented as part of a Base Station 110
as well as part of a User Device 120 or 130.
FIG. 2, numeral 200, is a block diagram illustrating a device in
accordance with the present invention. The communication receiver
in accordance with the present invention includes at least one
antenna (101) wherein the outputs of the antennas are each provided
to a receiving unit (201). The outputs of the receiving units (201)
are provided to at least one Antenna Combiner (202). The signals
from the receiving units (201) are also fed into the Combiner
Controller (210), which regulates the operation of the at least one
Antenna Combiner (202). The signals from the receiving units (201)
are also fed into the Channel Estimation Device (208). The Pilot
Symbol Generator (212) generates pilot symbol information that is
used by the Combiner Controller (210) to control the Antenna
Combiner (202). The pilot symbol information generated by the Pilot
Symbol Generator (212) is also used by the Channel Estimation
Device (208) to estimate the time-varying frequency responses of
the transmitting devices (110, 112, 120, 130, or 140, or any
combination thereof). The output of an Antenna Combiner (202) is
fed into an Information Decoding Unit (206), which decodes the
Antenna Combiner Output (204) and generates data information (213)
that was received by the Antennas (101).
FIG. 3, numeral 300, is a block diagram illustrating details of the
Antenna Combiner of the device of FIG. 2. Antenna Combiner (202) is
coupled to the receiving units (201), which in turn are coupled to
the antennas (101). In a preferred embodiment, the receiving units
(201) may include radio frequency pre-amplifiers, filters, and
other devices that can be used to convert the radio frequency
signal received by the antenna down to a digital stream of baseband
equivalent complex symbols. As shown in FIG. 2, the output of the
i'th receiving unit (201) (where i is an integer between 1 and M
inclusive, and M is the total number of antenna elements) is
mathematically denoted by y.sub.i (k), where k and i are integers,
and is provided to the antenna combiner (202) which can be in the
form of a plurality of complex multipliers (302) which multiply the
output of each receiving unit (201) by a complex weight (304),
mathematically denoted as w.sub.i (k), and a combiner (306) sums
the outputs of the plurality of complex multipliers (302). The
values of the complex weights (304) are controlled by the Combiner
Controller (210), which are described in more detail below.
FIG. 4, numeral 400, is a timing diagram illustrating the structure
of an information burst for a communication system with cyclic
prefixes (420) transmitted between a plurality of transmitting
devices (e.g., Base station 110, User Device 120, or 130) and a
receiving device (e.g., Base station 110, User Device 120, or 130).
A cyclic prefix (420) is a repetition of the last L.sub.CP (where
L.sub.CP is typically chosen to be longer than the expected channel
length in time-domain samples) data symbols right before a data
block (430). An information burst (410) includes a cyclic (420) and
at least one block (data interval), N (430). It should be noted
that by blocks it is meant the N symbols that are DFT'd into the
frequency domain for processing. The various blocks being
transmitted are representing by the integer "b " (440).
The channel estimation device (208) provides Doppler channel
estimates for the at least one desired transmitters that is used by
the Combiner Controller (210) to produce combining weights
utilizing the method and device of the present invention. The fixed
in time combining weight calculations for all communication systems
(that is: systems using a cyclic prefix and systems not using a
cyclic prefix) are expressed in FIG. 5 and FIG. 6, and the
calculations for the fixed in time combining weights for null
cyclic prefix communication systems are expressed in FIG. 7. The
term null cyclic prefix means that the cyclic prefix consists of
L.sub.cp zeros instead of the repeated symbols from the end of a
data block. A mathematical derivation of the combining weights is
now given.
The received M.times.1 (where M is the number of receivers)
time-domain signal on block b is modeled as ##EQU2##
where U is the number of transmitting devices, V.sub.T =(2V+1) is
the number of Doppler channels, L is the number of time taps in
each Doppler channel, h.sub.u,v (l) is transmitter u's v.sup.th
Doppler channel, b indicates the block number, N.sub.k is the
Doppler DFT size (typically chosen to be twice the size of the
total number of time-domain samples in a data burst), n.sub.b is
the absolute time reference of data block b (e.g., in a
communication system with regular cyclic prefixes, if data block 1
starts at time n.sub.1 =0, then data block b would be at time
n.sub.b =(b-1)(N+L.sub.cp) where L.sub.cp is the length of the
cyclic prefix), for systems with cyclic prefixes [(n).sub.N mean n
mod N]:
and for systems with no cyclic prefixes:
The frequency-domain received symbols on block b are given as:
##EQU3##
With some manipulation, Y(k,b) becomes: ##EQU4##
where ##EQU5##
The Null Doppler weights derived by assuming the received
frequency-domain signal is (for any communication system)
##EQU6##
frequency-domain Doppler channel, N(k,b) is an M.times.1 (M=# of
antennas) noise vector, and Z.sub.u,v (k,b) is ##EQU7##
The Null Doppler combining weights for transmitter u and Doppler
channel v are found as the solution to ##EQU8##
where it is assumed that (where E{X} means the expected value of
X):
while .delta.(n)=1 if n=0 and .delta.(n)=0
otherwise. The solution is w.sub.u,v(k)=(R.sub.T (k)).sup.-1
H.sub.u,v (k), where R.sub.T (k)=R(k)+R.sub.c (k), ##EQU9##
and R.sub.c (k) is the spatial correlation matrix of the corrupting
environment (in the preferred embodiment when there is no
significant unknown interference, R.sub.c (k)=.sigma..sub.n.sup.2
I.sub.M where .sigma..sub.n.sup.2 is the frequency-domain noise
power and I.sub.M is an M.times.M identity matrix).
An alternate set of combining weights, called the Zero-Forcing
Doppler combining weighs, can be found as the solution to W.sup.H
(k)G(k)=I.sub.UV.sub..sub.T , where I.sub.m is an m.times.m
identity matrix, V.sub.T is the total number of Doppler channels,
and W(k) and G(k) are: (M.times.UV.sub.T) G(k)=[H.sub.1,-V (k), . .
. , H.sub.1,V (k), H.sub.2,-V (k), . . . , H.sub.U,V (k)]
W(k)=[w.sub.1,-V (k), . . . , H.sub.1,V (k), H.sub.2,-V (k), . . .
, H.sub.U,V (k)].
Each column of W(k) contains one of the desired transmitter's
combining weights for one of the Doppler channels. The solution to
W.sup.H (k)G(k)=I.sub.U,V.sub..sub.T is given by the right pseudo
inverse of G(k): W(k)=G(k)(G.sup.H (k)G(k)).sup.-1.
The advantage that these Zero-Forcing Doppler weighs have over the
regular Null Doppler weights given above is that they have lower
computational complexity when M>UV.sub.T. The problems with the
Zero-Forcing Doppler weights are that they are not easily extended
to handle unknown interference, and no solution exists if UV.sub.T
>M. The fixed in time MMSE Doppler weights are given as the
solution to: ##EQU10##
The solution is:
where .sigma..sub.n.sup.2 is the frequency-domain noise power and:
##EQU11##
Because the fixed in time MMSE Doppler weights use a better
criterion for determining the combining weights, they have much
better BER performance than the Null Doppler and Zero-Forcing
Doppler weights.
FIG. 5 numeral 500, is a flow chart representation of fixed in time
combining weight calculations for any communication system, in
accordance with the present invention. These combining weights are
referred to as the Null Doppler combining weights. Providing
Doppler channel estimates for each transmitter, and a spatial
covariance matrix of a corrupting environment (510) from the
channel estimation device 208, a Null Doppler spatial covariance
matrix ##EQU12##
is calculated as a function of the Doppler channel estimates (520).
At block 530 a total Doppler spatial covariance matrix R.sub.T (k)
is then computed as a sum of the spatial covariance matrix of the
corrupting environment plus the Doppler spatial covariance matrix
using the aforementioned equation R.sub.T (k)=R(k)+R.sub.c (k).
Using the Null Doppler spatial covariance matrix and the total
Doppler spatial covariance solutions, (540) a combining weight is
computed at subcarrier k for at least one transmitter and at least
one Doppler channel as in the equation (w.sub.u,v (k)=(R.sub.T
(k)).sup.-1 H.sub.u,v (k)).
FIG. 6 numeral 600, is a flow chart representation of alternative
fixed in time combining weight, the Zero-Forcing combining weights,
calculations for any communication system, in accordance with the
present invention. The Doppler channel estimates for each
transmitter (610) provided from the channel estimation device 208,
are used to form the Doppler channel matrix for all desired
transmitters G(k) (M.times.UV.sub.T) G(k)=[H.sub.1,-V (k), . . . ,
H.sub.1,V (k), H.sub.2,-V (k), . . . , H.sub.U,V (k)] (620).
Finally in block 630, a combining weight is computed at subcarrier
k for at least one transmitter and at least one Doppler channel as
a function of the Doppler channel matrix for all desired
transmitters. The derived equation for 630 is W(k)=G(k)(G.sup.H
(k)G(k)).sup.-.
FIG. 7 numeral 700, is a flow chart representation of fixed in time
combining weight calculations for communication systems with null
cyclic prefixes, in accordance with the present invention.
Providing the Doppler channel estimates for each transmitter, and a
spatial covariance matrix of a corrupting environment (710) from
the channel estimation device 208, a Doppler spatial covariance
matrix is computed as a function of the Doppler channel estimates
and the frequency correlation function (720). The Doppler spatial
covariance matrix R(k) is equated for information bursts having
null cyclic prefixes as ##EQU13##
where the frequency correlation function, .alpha..sub.b (V), is
##EQU14##
At block 730, a total Doppler spatial covariance matrix is then
computed as a sum of the spatial covariance matrix of the
corrupting environment plus the Doppler spatial covariance matrix
(R.sub.T (k)=R(k)+R.sub.c (k)). A Doppler steering vector for the
at least one transmitter and at least one Doppler channel is
computed in block 740 as a function of the Doppler channel
estimates and the frequency correlation function ##EQU15##
With the total Doppler spatial covariance, the Doppler steering
vector for at least one transmitter and at least one Doppler
channel (750), a combining weight at subcarrier k is computed for
at least one transmitter and at least one Doppler channel utilizing
the equation (w.sub.u,v (k)=(R.sub.T (k)).sup.-p.sub.u,v (k)).
Once combining weights are found, the transmitted data can be found
by weighting the received frequency-domain data with the combining
weights. In equation form this is expressed as: X.sub.u,v
(k,b)=w.sub.u,v.sup.H (k)Y(k,b) where X.sub.u,v (k,b) is the
estimated frequency-domain symbol of user u for Doppler channel v.
To obtain an estimate of the time-domain transmitted symbols,
X.sub.u,v (k,b) needs to be brought back to the time domain and be
de-rotated by the conjugate of the v.sup.th Doppler sinusoid. In
equation form, this process is expressed in the following two
steps: First, the time-domain symbol estimates for user u and
Doppler channel v are: ##EQU16##
Then, the estimated time-domain symbols for user u are given as:
x.sub.u (n,b)=x.sub.u,v (n,b)e.sup.-j2.pi.v(n+n.sup..sub.b
.sup.)/N.sup..sub.k .
The present invention may be embodied in other specific forms
without departing from its spirit or essential characteristics. The
described embodiments are to be considered in all respects only as
illustrative and not restrictive.
* * * * *